1. Field of the Invention
This invention pertains generally to the characterization of atrial fibrillation by quantifying the spatiotemporal organization (STO) of electrical propagation during atrial fibrillation, and to using such STO to direct therapy.
2. Description of the Background Art
Atrial fibrillation is the most common sustained cardiac arrhythmia encountered in clinical practice, and affects as many as 5% of Americans over the age of 65. Atrial fibrillation is associated with symptoms such as palpitations, shortness of breath, and fatigue. In addition, it is associated with significant morbidity and mortality, including embolic stroke and symptoms related to loss of atrial mechanical function and atrioventricular synchrony. Furthermore, therapy commonly used in the treatment of atrial fibrillation also has the potential for significant morbidity and mortality. For example, antiarrhythmic therapy can result in proarrhythmia, whereas coumadin therapy may result in hemorrhagic complications.
Despite the high incidence of atrial fibrillation, its underlying mechanisms are not well understood. Around the turn of this century, several researchers suggested that atrial fibrillation was the result of single or multiple ectopic foci. In the 1920s, Lewis and Garrey suggested that a different mechanism, based on re-entry set up by localized areas of conduction block, instead might be responsible for the chaotic nature of electrograms recorded during atrial fibrillation.
In 1962, Moe published his widely known multiple wavelet hypothesis of atrial fibrillation. Moe said that the atria were fibrillating "when records of their electrical activity show rapid oscillations of irregular contour and duration, or when synchronous organized mechanical activity is replaced by fine irregular ripples, coursing without apparent pattern over the atrial surface." He also stated that any factor reducing the number of circulating wavelets will tend to increase the chances for spontaneous recovery. Moe's hypothesis of multiple circulating wavelets later was verified by Allessie and coworkers who used high-density epicardial mapping to evaluate atrial fibrillation. They noted that fibrillatory waveforms showed a temporal variation in cycle length at a given site and a spatial variation in cycle length at a given time.
At present there is a critical shortage of techniques for evaluation of atrial electrophysiologic substrate in patients prone to atrial fibrillation. This shortage results from two factors: first, analysis of fibrillatory electrograms is complicated by continual spatial and temporal variations in activation patterns and, second, detailed characterization of fibrillation typically requires measurement from a large number of endocardial or epicardial recording sites this is not practical for implementation in the cardiac electrophysiology laboratory or by an implanted device.
Past and present efforts to better understand the electrophysiology of patients with atrial fibrillation can be broken down into four categories: assessment of atrial vulnerability, related efforts in measurement of organization of ventricular fibrillation, measurement of organization in atrial fibrillation, and assessment of propagation direction.
Assessment of Atrial Vulnerability
The use of programmed stimulation in an attempt to induce atrial fibrillation has been used by several groups to evaluate susceptibility to fibrillation. A study by Fujiki demonstrated that patients with paroxysmal atrial fibrillation and vulnerable atria (defined as induction of repetitive atrial firing due to a single atrial extrastimulus) had shorter atrial effective refractory periods (ERPs) than patients without atrial vulnerability. Electrograms of the premature beat were also longer and more fractionated in patients with atrial vulnerability. The future clinical implications of measurement of atrial vulnerability remain unclear.
Measurement of Organization in Ventricular Fibrillation
The concept of measuring the spatiotemporal organization of arrhythmias has been explored more extensively in the case of ventricular fibrillation than in atrial fibrillation. Ropella and coworkers compared the magnitude-squared coherence (MSC), ventricular rate, and irregularity of cycle length during induced ventricular arrhythmias. Differentiation of monomorphic ventricular tachycardia (VT) from polymorphic VT was possible using MSC, more difficult using ventricular rate, and not possible using beat-to-beat irregularity. Sih and coworkers computed pair-wise values of MSC from an array of unipolar electrodes. They noted that MSC decreased as a function of distance for all investigated rhythms, but the most pronounced effects were in the case of fibrillation. Bayly and coworkers measured correlation length in pigs during ventricular fibrillation and found that correlation length varied with the duration of fibrillation. Damle et al. analyzed the effects of chronic and subacute infarction on the organization of ventricular fibrillation in dogs. The degree of linking was lower in the animals without an infarction, suggesting a lower degree of organization during ventricular fibrillation.
Measurement of Organization in Atrial Fibrillation
Early analysis of atrial fibrillation was limited to characteristics of the surface electrocardiogram. Subsequent efforts categorized endocardial electrograms on the basis of morphology, average rates of local activation, rate variance, and distribution of activation intervals. Wells and coworkers recorded epicardial bipolar electrograms in patients developing atrial fibrillation following cardiac surgery. They found that it was possible to categorize the fibrillation into four types on the basis of electrogram organization and morphology. Konigs and coworkers described three types of atrial fibrillation in patients according to the number of circulating wavelets present in patients undergoing surgery for Wolf-Parkinson-White Syndrome. Although this study provided evidence for varying degrees of organization of fibrillation between different patients, it did not evaluate temporal variations in individual patients.
Botteron and Smith computed an activation space constant from endocardial electrogram recordings. Their work is notable because it goes beyond simple analysis of temporal characteristics of electrograms. Instead, it attempts to fit the measured spatial and temporal data to a single function, from which a descriptive spatial statistic is obtained. The function, which takes distance and time gradients as time-dependent variables, is an exponentially decaying curve of cross-correlation coefficients. This approach is based on the expectation that signals will be less correlated when acquired from sites separated by greater distances. They found that the spatial scale of atrial organization was shorter in patients with chronic fibrillation, longer in patients with newly acquired fibrillation, and of an intermediate value in patients with a history of paroxysmal atrial fibrillation.
Measurement of Propagation Direction
Other groups have examined direction of propagation during fibrillation. Gerstenfeld et al. used an orthogonal catheter to demonstrate that the relative direction of atrial activation could remain constant for six or more consecutive atrial activations. This finding showed that not only is atrial reentry likely, but that it has time-varying degrees of spatial organization, presumably the result of the combination and destruction of individual wavelets. Recently, Holm and coworkers also investigated propagation direction using bipolar electrograms recorded from 56 epicardial locations. They found three types of preferable activation patterns and discovered that focal atrial activation occurred as a repetitive phenomenon.
Despite the extensive research noted above, there is a clear lack of tools to assist the clinician in determining which of these treatment strategies is best suited for a given patient. This problem is likely to be compounded as new treatments continue to emerge. In addition to the immediate need for optimizing patient treatment, there is a longer-term need for a better understanding of the electrophysiological mechanisms responsible for atrial fibrillation. The present invention satisfies those needs, as well as others, and overcomes the drawback of prior detection methodologies that rely on a large number of epicardial recording sites to quantify spatiotemporal organization and which are not feasible in the cardiac electrophysiology laboratory or for implementation by implanted devices.